An improved active power direction method for harmonic source identification

2020 ◽  
Vol 42 (13) ◽  
pp. 2569-2577
Author(s):  
Pragya Joshi ◽  
Sachin K Jain

Due to significant increment in harmonic polluting loads in the power system, there has been enhanced attention of the power professionals towards the estimation of harmonic signals and identification of their sources in the system. Harmonic source identification is an important step for proper accountability, monitoring, and mitigation of any harmonic pollution. The active power direction (APD) method is one of the conventional approaches for harmonic source detection in the distribution system. Although it is simple and easy to implement, serious concerns were raised on its validity, as the direction of active power is dependent on the phase angle. In this paper, APD is augmented with distorting and non-distorting power to improve its accuracy and reliability for harmonic source identification. The distorting and non-distorting portions of the loads are separated, and the distorting and non-distorting powers are calculated at each node. These calculated powers, in addition to the direction of the harmonic active power, are used to formulate the logic required for deciding the severity index at each node. The validity of the method has been tested on a single-phase network, an IEEE-5 bus system, and an IEEE-14 bus system. It has been observed that the proposed method provides good results than conventional APD with the same measurement requirement.

2017 ◽  
Vol 40 (12) ◽  
pp. 3415-3423 ◽  
Author(s):  
Preeti Jain ◽  
Atul Kumar Tiwari ◽  
Sachin Kumar Jain

With proliferation of power electronics devices in the distribution system, harmonic distortion has become one of the major power quality (PQ) problems. In evolving the liberalized electricity market, it becomes necessary to develop suitable methods to allocate the responsibilities for the harmonic distortion to improve the PQ. This paper presents a new technique for harmonic source identification, which is based on total harmonic power (THP) method using estimation of signal parameters via rotational invariance technique (ESPRIT). Traditionally, harmonic powers for THP method is computed using Fourier transform, which inherits serious drawbacks of the discrete and fast Fourier transform, namely, inaccuracy owing to poor spectral resolution, spectral leakage, and so forth. Simulation results have been presented for different distribution system configurations and conditions, which confirms the improved capabilities of the proposed method in harmonic source identification.


Author(s):  
Fangwei Xu ◽  
Honggeng Yang ◽  
Jinshuai Zhao ◽  
Zhiqi Wang ◽  
Yamei Liu

2020 ◽  
Vol 19 (2) ◽  
pp. 40-45
Author(s):  
Maryam Nabihah Zaidi ◽  
Dalila Mat Said ◽  
Aida Fazliana Abdul Kadir ◽  
Nasarudin Ahmad

The growing use of non-linear loads in the electrical systems has made harmonics a serious problem. Harmonic disturbance leads to degradation of power quality by deforming the current or voltage waveforms, thus, necessitating the effective techniques for harmonics detection.  The purpose of this study is to propose a method for a single harmonic source identification in power distribution system by implementing a network impedance technique, and optimize the meters allocation by optimum meter placement algorithm (OMPA). The main advantage of this technique is that it results in enhanced accuracy with minimum vulnerability towards deviations in the measurements. Moreover, it minimizes the number of nodes for meter allocations, thereby resulting in economic advantages. To validate the results and effectiveness of the proposed methodology, a standard IEEE 13-Bus industrial network is designed using ETAP software and the algorithm is developed in MATLAB software. The validation of proposed algorithm OMPA is done by comparing its results with Monte Carlo Algorithm (MCA) technique. The results show that without any deviation in the network impedances, OMPA gives 89% accuracy as compared to 75% accuracy of MC. With the deviations in the harmonic impedances, the accuracy of both algorithms is decreased. For the deviation value ꝺ = 1-13 in the harmonic impedances, the overall accuracy of OMPA stays at 75%, while that of MCA drops down to 56%. The developed algorithm OMPA is not only better in performance in harmonics identification with minimum number of meters, but also shows more resistance to the variations in the harmonic impedances as compared to MCA.


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